class_docstr: A wrapper around a C++ OrderedDict.
  
  It dynamically evaluates the OrderedDict getter on a bound C++ module, such
  that new changes on the C++ side are picked up. Otherwise accessing e.g.
  ``cpp_module._parameters`` just once would get a frozen copy of the parameters
  at the time of access. ``torch.nn.Module`` accesses ``_parameters`` et al. via ``self.__dict__``
  so using properties does not work.
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code: def values(self):
      return self.cpp_dict.values()
  
file_path: pytorch/torch/nn/cpp.py
imports: from torch import nn
label_desc: Use image node_id 5 for calling the OrderedDictWrapper obj's underlying member method code with example usage: obj.values() and returns: self